Knowing and/or experiencing: a critical examination of the reflective models of John Dewey and Donald Schön
Bibliographic record
Abstract
In this paper, I take issue with the overuse of reflective practice in teacher education, arguing that the term ‘reflection’ is often utilized without a comprehensive understanding of its quite diverse parentage. In efforts to clarify the term, I trace the ideological lineage of reflective practice in education, detailing the rationalist-technicist model offered in the work of John Dewey and the experiential-intuitive model as it appears in the work of Donald Schön, highlighting the key differences in their respective approaches to reflection through critique. I demonstrate that both models bifurcate knowledge and experience, privileging the former at the expense of the latter. I conclude with a brief exploration of Van Manen’s tacit knowing and its potential for reflective practice in teacher education. Ultimately, this work cautions against an uncritical adoption of reflective models, stressing that in doing so, the very spirit of reflective practice can be undermined.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.020 | 0.113 |
| Scholarly communication | 0.017 | 0.026 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".